Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: determining, by a processor, a first therapy program that comprises a set of therapy parameters values; generating, by the processor, an algorithmic model of a therapy field based on the first therapy program, the algorithmic model representing where therapy will propagate from a therapy system delivering therapy according to the first therapy program; and automatically determining, by the processor, a second therapy program that increases an operating efficiency of the therapy system while substantially maintaining the therapy field.
A method implemented by a processor involves: First, it determines a therapy program consisting of a set of therapy parameter values (like voltage, pulse width, electrode configuration). Second, it generates a computational (algorithmic) model of the therapy field resulting from applying this therapy program using a therapy system. The model predicts where the therapy will propagate. Third, the processor automatically finds a different therapy program that increases the therapy system's operating efficiency (e.g., uses less power, operates at better voltage) while substantially keeping the therapy field the same as before.
2. The method of claim 1 , further comprising controlling, by the processor, the therapy system to deliver therapy to a patient according to the second therapy program.
The method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field) also includes controlling the therapy system to deliver therapy to the patient using this second, more efficient therapy program. So, the system actively applies the improved therapy settings.
3. The method of claim 1 , wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, the method further comprising generating, by the processor, a second algorithmic model of a second therapy field representing where therapy will propagate from the therapy system based on the second therapy program.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), the algorithmic model is actually a first model of a first therapy field. The method goes further by generating a second algorithmic model of a second therapy field. This second model represents where the therapy will propagate when using the second, more efficient therapy program. This allows for comparison of the two therapy fields.
4. The method of claim 3 , further comprising presenting the first algorithmic model of the first therapy field and the second algorithmic model of the second therapy field to a user.
The method described previously (generating first and second therapy field models based on original and efficient therapy programs) includes presenting both the first (original program) and second (efficient program) therapy field models to a user, likely a clinician. This allows the user to visualize and compare the therapy fields generated by each therapy program. This could be done through a graphical interface.
5. The method of claim 1 , wherein automatically determining the second therapy program comprises automatically determining the second therapy program based on at least one of an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), the automatic determination of the second, more efficient therapy program is based on at least one of several clinical curves or models: an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model. These curves provide data regarding how different parameter settings affect therapy outcome.
6. The method of claim 5 , wherein the at least one amplitude-duration curve, dose-response curve, strength-duration curve, or 3D depolarization field model is configured based on at least one of a patient condition, a desired therapeutic outcome, or a tissue characteristic of a target delivery site.
In the method described previously (automatically determining a second therapy program based on clinical curves/models), the amplitude-duration curve, dose-response curve, strength-duration curve, or 3D depolarization field model being used is configured based on at least one of: the patient's condition, the desired therapeutic outcome, or the tissue characteristics of the target delivery site. The therapy is therefore personalized/optimized for the patient.
7. The method of claim 1 , wherein the second therapy program increases the operating efficiency of the therapy system by at least one of decreasing power consumption or operating at an efficient amplitude determined based on a voltage multiplier level.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), the second therapy program increases operating efficiency by either decreasing power consumption or operating at an efficient amplitude. This amplitude is determined based on voltage multiplier levels in the therapy system, indicating the system is optimizing voltage conversion for power savings.
8. The method of claim 1 , wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, the method further comprising generating a second algorithmic model of a second therapy field based on the second therapy program, wherein substantially maintaining the therapy field comprises maintaining a difference between the first therapy field and the second therapy field below a threshold value, wherein the threshold value defines a maximum allowable change in at least one field characteristic.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), the algorithmic model is actually a first model. The method also generates a second model based on the second therapy program. Substantially maintaining the therapy field means keeping the difference between the first and second therapy fields below a certain threshold. This threshold represents the maximum acceptable change in at least one therapy field characteristic.
9. The method of claim 8 , wherein the at least one field characteristic comprises at least one of a centroid, a volume, an amplitude, a width at a defined amplitude, or a charge density.
In the method described previously (maintaining a difference between first and second therapy fields below a threshold), the field characteristic being monitored includes at least one of: the centroid (center point), the volume, the amplitude, the width at a defined amplitude, or the charge density of the therapy field. These provide quantifiable measures of the shape, strength, and extent of the therapy.
10. The method of claim 8 , wherein the threshold value comprises a weighted threshold of a plurality of field characteristics.
In the method described previously (maintaining a difference between first and second therapy fields below a threshold), the threshold is actually a *weighted* threshold. This means multiple field characteristics are considered, and each contributes differently to the overall threshold based on assigned weights reflecting clinical importance.
11. The method of claim 1 , wherein generating the algorithmic model of the therapy field comprises representing where therapy will propagate from the therapy system based upon the first therapy program and an anatomical data set.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), generating the algorithmic model means representing where the therapy will propagate based not only on the therapy program parameters, but also an anatomical data set representing patient geometry or tissue properties.
12. The method of claim 11 , wherein the anatomical data set comprises at least one of an anatomical image of a patient, a reference anatomical image, an anatomical atlas, or a tissue conductivity data set.
In the method described previously (generating an algorithmic therapy field model based on therapy parameters and anatomical data), the anatomical data set is at least one of: an anatomical image of the patient (e.g. MRI, CT), a reference anatomical image (e.g. from a standard atlas), an anatomical atlas, or a tissue conductivity data set. This provides spatial context for the therapy field model.
13. The method of claim 1 , wherein the therapy parameters comprise at least one of an electrode combination, pulse width, frequency or amplitude.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), the therapy parameters include at least one of: which electrodes are used, the pulse width, the frequency, or the amplitude of the therapy signal. These are the adjustable settings of the therapy system.
14. The method of claim 1 , wherein the algorithmic model of the therapy field comprises at least one of a two dimensional algorithmic model or a three dimensional algorithmic model.
In the method described previously (determining a first therapy program, generating a therapy field model, automatically determining a second more efficient therapy program that maintains the therapy field), the algorithmic model of the therapy field is either a two-dimensional or a three-dimensional representation.
15. A therapy system comprising: a medical device configured to deliver a therapy to a patient according to a first therapy program that comprises a first set of therapy parameters; and a processor configured to: generate an algorithmic model of a therapy field based on the first therapy program, wherein the algorithmic model represents where the therapy will propagate from the medical device delivering therapy according to the first therapy program, and automatically determine a second therapy program that increases an operating efficiency of the therapy system while substantially maintaining the therapy field.
A therapy system includes: A medical device configured to deliver therapy based on a first therapy program (with parameters such as voltage, pulse width, electrode selection). The system *also* includes a processor that: generates an algorithmic model of the therapy field resulting from the first therapy program, modeling where therapy will propagate. The processor *also* automatically determines a second therapy program that increases the system's operating efficiency (e.g., lower power) while keeping the therapy field substantially the same.
16. The therapy system of claim 15 , wherein the medical device is configured to deliver therapy from the therapy system to the patient according to the second therapy program.
The therapy system previously described (medical device, processor generating efficient therapy programs) includes the medical device delivering therapy according to the *second*, more efficient, therapy program. Therefore, the system not only finds a better therapy setting, but automatically uses it.
17. The therapy system of claim 15 , wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, and wherein the processor is configured to generate a second algorithmic model of a second therapy field that represents where the therapy will propagate from the therapy system based on the second therapy program.
In the therapy system described previously (medical device, processor generating efficient therapy programs), the therapy field model is actually a first model. The processor also generates a *second* algorithmic model of a second therapy field. This second model represents where the therapy propagates based on the second, more efficient, therapy program. This enables comparison of the two fields.
18. The therapy system of claim 17 , further comprising a user interface that presents the first algorithmic model of the first therapy field and the second algorithmic model of the second therapy field to a user.
The therapy system previously described (generating first and second therapy field models based on original and efficient therapy programs) includes a user interface that presents *both* therapy field models (original and efficient) to the user. This allows visualization and comparison, aiding in clinical decision-making.
19. The therapy system of claim 15 , wherein the processor is configured to automatically determine the second therapy program based on at least one of at least one of an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model.
In the therapy system described previously (medical device, processor generating efficient therapy programs), the processor automatically determines the second therapy program based on at least one of: an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model. These curves provide data regarding how different parameter settings affect therapy outcome.
20. The therapy system of claim 19 , wherein the at least one amplitude-duration curve, dose-response curve, strength-duration curve, or 3D depolarization field model is based on at least one of a patient condition, a desired therapeutic outcome, or a tissue characteristic of a target delivery site.
In the therapy system previously described (automatically determining a second therapy program based on clinical curves/models), the amplitude-duration curve, dose-response curve, strength-duration curve, or 3D depolarization field model is based on at least one of: the patient's condition, the desired therapeutic outcome, or the tissue characteristics of the target delivery site. The automated program selection adapts to patient-specific needs.
21. The therapy system of claim 15 , wherein the second therapy program increases the operating efficiency of the therapy system by at least one of decreasing power consumption or operating at an efficient amplitude determined based on voltage multiplier levels.
In the therapy system described previously (medical device, processor generating efficient therapy programs), the second therapy program increases efficiency by either decreasing power consumption or operating at an efficient amplitude. This efficient amplitude is determined based on voltage multiplier levels within the system, optimizing the power conversion.
22. The therapy system of claim 15 , wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, wherein the processor is configured to generate a second algorithmic model of a second therapy field based on the second therapy program, and wherein substantially maintaining the therapy field comprises maintaining a difference between the first therapy field and the second therapy field below a threshold value, wherein the threshold value comprises a maximum allowable change in at least one field characteristic.
In the therapy system previously described (medical device, processor generating efficient therapy programs), the initial algorithmic model represents a first therapy field. The processor generates a second model based on the second, efficient program. Substantially maintaining the therapy field means the difference between the first and second therapy fields remains below a threshold. This threshold represents the maximum acceptable change in at least one field characteristic.
23. The therapy system of claim 22 , wherein the at least one field characteristic comprises at least one of a centroid, an area, an amplitude, a width at a defined amplitude, or a charge density.
In the therapy system described previously (maintaining a difference between first and second therapy fields below a threshold), the field characteristic being monitored is at least one of: a centroid, an area, an amplitude, a width at a defined amplitude, or a charge density. These represent key features of the therapy field distribution.
24. The therapy system of claim 22 , wherein the threshold value comprises a weighted threshold of a plurality of field characteristics.
In the therapy system described previously (maintaining a difference between first and second therapy fields below a threshold), the threshold comprises a *weighted* threshold across multiple field characteristics, allowing prioritization based on clinical relevance.
25. The therapy system of claim 15 , wherein the processor is configured to generate the algorithmic model of the therapy field based upon the set of therapy parameters and an anatomical data set.
In the therapy system described previously (medical device, processor generating efficient therapy programs), the processor generates the algorithmic model of the therapy field based on the therapy parameter *and* an anatomical data set. The anatomical data set represents tissue properties and/or patient geometry.
26. The therapy system of claim 15 , wherein the medical device comprises the processor.
In the therapy system described previously (medical device, processor generating efficient therapy programs), the medical device *itself* includes the processor that generates the therapy field models and determines the efficient therapy program.
27. The therapy system of claim 15 , further comprising a medical device programmer that comprises the processor.
The therapy system described previously (medical device, processor generating efficient therapy programs) *also* includes a medical device programmer. This programmer *includes* the processor that generates the therapy field models and determines the efficient therapy program. The programmer is therefore separate from the implantable device.
28. The therapy system of claim 15 , wherein the medical device is configured to deliver at least one of electrical stimulation therapy or a therapeutic agent to the patient.
In the therapy system previously described (medical device, processor generating efficient therapy programs), the medical device delivers at least one of: electrical stimulation therapy *or* a therapeutic agent to the patient.
29. A system comprising: means for determining a first therapy program that comprises a set of therapy parameters values; means for generating an algorithmic model of a therapy field based on the first therapy program, the algorithmic model representing where therapy will propagate from a therapy system delivering therapy according to the first therapy program; and means for automatically determining a second therapy program that increases an operating efficiency of the therapy system while substantially maintaining the therapy field.
A system comprises: a means for determining a first therapy program (i.e., a module or device that finds initial therapy settings); a means for generating a therapy field model based on the initial program (i.e., a module that calculates therapy propagation); and a means for automatically determining a second therapy program with increased efficiency while maintaining the therapy field (i.e., a module for therapy optimization).
30. The system of claim 29 , wherein the means for automatically determining the second therapy program determines the second therapy program based on at least one of at least one of an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model.
The system previously described (means for determining therapy programs and models) includes the means for automatically determining the second therapy program being based on at least one of: an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a 3D depolarization field model.
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October 17, 2017
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